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This paper investigates factors associated with variation in daily total (electricity and gas) energy consumption in domestic buildings using linked pre-COVID-19 smart meter, weather, building thermal characteristics, and socio-technical survey data covering appliance ownership, demographics, behaviours, and attitudes for two nested sub-samples of 1418 and 682 British households selected from the Smart Energy Research Laboratory (SERL) Observatory panel. Linear mixed effects modelling resulted in adjusted R2 between 63% and 80% depending on sample size and combinations of contextual data used. Increased daily energy consumption was significantly associated (p -value < 0.05, VIF < 5) with: households living in buildings with more rooms and bedrooms, that are older, more detached, have air-conditioning, and experience colder (more heating degree days) or less sunny weather; households with more adult occupants, more children, older adult occupants, higher heating temperature setpoints, and that do not try to save energy. The results demonstrate the value of smart meter data linked with contextual data for improving understanding of energy demand in British housing. Accredited UK researchers are invited to apply to access the data, which has recently been updated to include over 13,000 households from across Great Britain. This paper provides guidance on appropriate methods to use when analysing the data. [ABSTRACT FROM AUTHOR]

• A new methodology to investigate the impact of thermal mass is defined. • The use of unrepresentative boundary conditions could lead to inaccurate conclusions. • High thermal mass helps to decrease and regulate the internal temperature. • High thermal mass could increase energy use in the summer and winter seasons. • Isolating thermal mass through internal insulation results in better energy performance than external insulation. Contradictory conclusions have been reported on whether thermal mass reduces or increases energy demand in hot and cold climates. A novel approach to measuring the impact of thermal mass on the building's energy consumption is presented. The method aims to better represent reality and applies two different control conditions simultaneously in a numerical model: the first condition, which has been used in past studies, adjusts the internal boundary condition based on the time duration of heating/cooling activation (simulating an occupancy pattern) and the second, which has not been used in past studies, adjusts the internal boundary condition based on both the time duration and the internal temperature (simulating an occupancy pattern and the thermostatic control system). When investigating the impact of thermal mass on the internal temperature in a scenario where no heat is transferred into the building, the high thermal mass outperforms the low thermal mass, showing a time-shifting effect, long time lag, and small decrement factor. However, when modelled using the method presented in this paper, high thermal mass results in greater energy consumption during summer and winter periods in Saudi Arabia. During transition seasons where temperature swings occur on either side of the indoor set-point temperatures, thermal mass reduces thermal transmission. The impact of thermal mass is also investigated for several climatic conditions in Saudi Arabia. Simulation results show that an internally exposed thermal massive wall section results in greater energy consumption when compared to a similar building with isolated thermal mass (i.e. insulated internally). This is due to the fact that even though the internal temperature inside the building is being cooled/warmed up to the set-point, the thermal mass continues to transfer heat that is absorbed by the building's fabric from/to the interior, placing a greater demand on the cooling/heating system. Over the course of a year, however, the impact of thermal mass is negligible when compared to other factors, such as the insulative properties of the building's fabric. [ABSTRACT FROM AUTHOR]